A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

The paper opens with observations that NoSQL databases are generally built to handle certain data models. Tencent admits it ran several of them to power its fleet of products – social networks ...

RDF is a graph data model that has been around since 1997. It's a W3C standard, and it's used to power schema.org and Open Graph, among other things. Plus, there's a bunch of RDF-based graph ...

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

DataStax Enterprise (DSE) is an example of a multi-model database, since at its core it supports Cassandra’s partitioned row store (tabular) model, with a graph abstraction built on top of that .

Graph neural networks. Graph neural networks will be a major trend in 2021, Josifovski predicted. At its core, the deep learning paradigm is a different way of structuring data, like images, and ...

One of the best-known graph databases is Neo4j, which recently announced support for the enterprise version of its cloud-hosted service, Aura, on Azure.Available in the Azure Marketplace, it’s a ...

Graph database startup TigerGraph Inc. today announced a major update to its flagship cloud platform with the Savanna release, bringing with it six times faster network deployments and dozens of other ...

The graph database is popular with social networks, ... The tool can run more than 60 different graph algorithms, ... and many offer hybrid models.